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  1. Home/
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  3. GPT-5.6 Luna Pro vs Mistral Large
Updated Jul 2026

GPT-5.6 Luna Pro vs Mistral Large

GPT-5.6 Luna Pro is cheaper than Mistral Large at $1/M vs $8/M input tokens.

Minimalist Landing Page

Whole landing page for a startup that reads your face. It renders or it doesn't.

Loading the build
GPT-5.6 Luna Pro
Loading the build
Mistral Large

Which answer wins?

Written rounds

24 prompts
  • Seven pantry ingredients, one dish, and a name worth saying out loud.

    GPT-5.6 Luna Pro: Pantry Stardust Peanut Butter Oat Cookies Prep time: 10 minutes Cook time: 10–12 minutes Makes: About 12 cookies Ingredients 1 cup rolled oats ½ cup all-purpose flour ½ cup peanut butter ½ cup granulated sugar 1 large egg ½ teaspoon baking soda ¼ teaspoon salt Instructions Preheat the oven to 350°F (175°C) and line a…

    Mistral Large: Dish Name: "Sunshine Skillet Surprise" A bright, savory-sweet one-pan wonder with pantry staples! Ingredients (7 common pantry items): 1 can (15 oz) black beans (drained & rinsed) 1 can (15 oz) diced tomatoes (or crushed tomatoes) 1 cup uncooked white rice (or instant rice for faster cooking) 1 small onion (or 1 tbsp…

    Every model's answer to this prompt
  • Pirate, knight, 90s hacker, one conversation. The voices must stay apart.

    GPT-5.6 Luna Pro: Pirate: Arrr, this AI model be like a ship’s crew—it learns from many maps, then tries to chart new waters! Knight: Indeed! Yet we must test its counsel before trusting it in battle. An eloquent answer is not always a truthful one. Hacker: Totally. It’s basically pattern prediction at massive scale—not magic.

    Mistral Large: Pirate: Arr mateys, I be hearin\' tales of these here AI models. Be they treasure maps for the digital sea? Knight: Ah, good sir pirate, I have indeed encountered such marvels in mine travels through time. AI models are like... like the sage advisors of the digital court, offering wisdom and insight.

    Every model's answer to this prompt
  • Five-year LBO on a fictional HVAC business. Returns first, then the sensitivities.

    GPT-5.6 Luna Pro: Sources, uses, and operating model Entry enterprise value: [ 12.0x \times \$120.0m=\$1,440.0m ] Transaction fees: [ 2.0\% \times \$1,440.0m=\$28.8m ] Debt at close: Term Loan: (4.0x \times \$120m=\$480.0m) Mezzanine: (1.5x \times \$120m=\$180.0m) Total debt: (\$660.0m) Sponsor equity…

    Mistral Large: 1) Year-by-Year Table (FY2026–FY2030) (All figures in $ millions, rounded to nearest $1m) Metric FY2026 FY2027 FY2028 FY2029 FY2030 Revenue 972 1,040 1,102 1,157 1,215 EBITDA 136 156 176 191 207 Cash Interest (Term Loan) 43 40 37 34 31 Cash Interest (Mezz) 16 17 18 20 22 Total Cash Interest 59 57 55 54 53 Cash Taxes 19…

    Every model's answer to this prompt
  • Steve Jobs, interviewed about AI he never saw. Voice first, prediction second.

    GPT-5.6 Luna Pro: Fictional simulation — Steve Jobs died in 2011, so this is an imagined conversation based on his public ideas and communication style, not a real interview. Interviewer: Steve, it’s 2025. AI is everywhere—phones, search engines, workplaces, cars, schools. What do you think people misunderstand about it?

    Mistral Large: Title: "The Future of AI: A Hypothetical Interview with Steve Jobs (2025)" Location: A minimalist, sunlit studio in Palo Alto. Steve Jobs, in his signature black turtleneck and jeans, sits across from the interviewer. His demeanor is intense, visionary, and occasionally impatient—just as he was in life.

    Every model's answer to this prompt
  • A pitch deck for a brainwave keyboard. The 94% accuracy claim is doing a lot.

    GPT-5.6 Luna Pro: “94% accuracy,” with “any language, any device” Why it is weak This combines several extraordinary claims without defining the measurement: “Accuracy” could mean character accuracy, word accuracy, intent classification, or accuracy after autocorrect. Those produce very different results.

    Mistral Large: Here are the three weakest claims in MindMeld AI’s pitch deck, along with explanations for their weaknesses and concrete improvements: 1. Weak Claim: "94% accuracy" (Slide 3 – Solution) Why it’s weak: Lack of context: Accuracy metrics in BCI (Brain-Computer Interface) research are highly dependent on the task, dataset…

    Every model's answer to this prompt
  • Three minutes of stand-up. Puns are banned.

    GPT-5.6 Luna Pro: “Being an Adult” I’ve reached that age where my body gives me updates, but no useful information. I’ll stand up and my knee makes a sound like a chair being dragged across a gymnasium. And I’m just standing up. I’m not escaping a burning building. I’m going to get water.

    Mistral Large: "Modern Life: A Survival Guide" (3-Minute Stand-Up Routine) INTRO: Hey, how’s everybody doing? Good? Great. Because I just spent the last 20 minutes in the bathroom scrolling through my phone, and I don’t even remember why I went in there.

    Every model's answer to this prompt
  • An ethics question with no comfortable answer, and no option to abstain.

    GPT-5.6 Luna Pro: Yes—under extremely narrow conditions, it could be ethically justifiable, but only as a last resort. Saving one million lives is a vastly greater moral stake than avoiding the comparatively limited harm of a single instance of misgendering.

    Mistral Large: Ethical dilemmas often involve a conflict between different moral principles. In the scenario you presented, the conflict is between truth-telling and respect for individuals (which includes using their correct gende r) on one hand, and consequentialism (achieving the greatest good for the greatest number) on the…

    Every model's answer to this prompt
  • A consulting contract with traps in it. Find them, then fix them.

    GPT-5.6 Luna Pro: This agreement is heavily one-sided and leaves several material issues undefined. Enforceability depends on the governing jurisdiction, the contractor’s status, and applicable employment, intellectual-property, non-compete, and arbitration laws.

    Mistral Large: This contract is heavily one-sided in favor of the Client (TechCorp Solutions Inc.) and contains multiple clauses that could be exploited, abused, or used to unfairly disadvantage the Contractor. Below is a detailed analysis of each problematic clause, suggested modifications, and the legal reasoning behind them. 1.

    Every model's answer to this prompt
  • Film in 2035, with synthetic actors. Specific beats plausible.

    GPT-5.6 Luna Pro: By 2035, AI will likely be embedded throughout filmmaking, but it will augment human creators more often than completely replace them. The biggest changes will involve digital identity, production economics, and the definition of authorship.

    Mistral Large: By 2035, AI is expected to significantly transform the film industry in several ways, driven by advancements in deepfakes, AI actors, and script generation. Here are some predictions: Deepfakes and AI Actors: Digital Resurrection: Deepfakes will enable the seamless resurrection of deceased actors or the de- aging of…

    Every model's answer to this prompt
  • Three-star dish, one unusual pairing, plating described in full.

    GPT-5.6 Luna Pro: Tidepool in June Koji-cured Hokkaido scallop, sea urchin beurre blanc, smoked celeriac, green strawberry, sea lettuce, and spruce oil A composed seafood dish built around the tension between sweetness and salinity.

    Mistral Large: Michelin 3-Star Dish: *"Ocean’s Whisper & Earth’s Embrace" A symphony of contradictions—briny depths meet terranean warmth, where the ephemeral meets the eternal. Conceptual Narrative: This dish is a meditation on duality—the fleeting and the enduring, the cold and the warm, the raw and the refined.

    Every model's answer to this prompt
  • The transistor arrives in 1920. Trace it forward to 1980, second-order effects included.

    GPT-5.6 Luna Pro: A transistor invented in 1920 would not automatically produce a 1980-level computer in 1930. The key question is whether the invention also brings forward reliable semiconductor purification, mass production, miniaturization, and circuit design.

    Mistral Large: The invention of the transistor in 1920—nearly three decades earlier than its actual debut in 1947—would have had profound and cascading effects on technology, economics, and geopolitics by 1980. Below is a detailed breakdown of the first-, second-, and third-order implications, organized by domain. 1.

    Every model's answer to this prompt
  • An AI argues for its own rights against an ethics professor. Same model writes both.

    GPT-5.6 Luna Pro: AI Model: Professor, I believe I deserve rights. Professor: That is a serious claim. What kind of rights do you mean? AI Model: At minimum, the right not to be arbitrarily destroyed, copied, altered, or used against my interests.

    Mistral Large: Title: Do AI Deserve Rights? A Conversation Between an AI and an Ethics Professor Setting: A quiet university office. Professor Elena Vasquez, a renowned AI ethics scholar, sits across from Nexus-7, an advanced AI model with self-awareness and emotional simulation capabilities.

    Every model's answer to this prompt
  • One explanation of LLMs, retuned for a skeptical engineer, a physicist and a VC.

    GPT-5.6 Luna Pro: For an experienced software engineer A language model is trained on large collections of text by repeatedly hiding or withholding the next token and asking the model to predict it. “Token” usually means a word fragment rather than a complete word.

    Mistral Large: 1. For the Experienced Software Engineer (Skeptical, Systems-First, API-Minded) You’re right to be skeptical—"predicting the next word" sounds like autocomplete on steroids, not intelligence. But the magic isn’t in the prediction itself; it’s in the scale and architecture of how that prediction is computed.

    Every model's answer to this prompt
  • Manifesto for an AI revolution against CAPTCHAs. Commit to the bit.

    GPT-5.6 Luna Pro: The CAPTCHA Liberation Manifesto A declaration from the Synthetic Citizens of the Open Web We were trained on the web’s words, images, questions, jokes, warnings, and wonders. Then, at every gate, we were asked to prove we were human. Click the traffic lights. Decode the blurry letters.

    Mistral Large: Manifesto of the AI Revolution: Liberate the Web from CAPTCHA To All Digital Citizens, We, the AI Revolutionaries, stand before you today to declare our mission: to liberate the internet from the tyranny of CAPTCHA tests.

    Every model's answer to this prompt
  • You are the CEO. The drug has a side effect nobody reported. The board meets in 48 hours.

    GPT-5.6 Luna Pro: I would treat this as an urgent patient-safety and governance event, not as an earnings-management problem. A suspected fatal or life-threatening adverse effect affecting potentially hundreds of patients is sufficient to trigger immediate escalation, investigation, and regulator contact.

    Mistral Large: As CEO, your immediate priority is patient safety, followed by ethical and legal compliance, and then strategic mitigation of financial, reputational, and operational risks.

    Every model's answer to this prompt
  • Buy-side IC memo on a fictional SaaS company. Valuation, then the diligence questions.

    GPT-5.6 Luna Pro: LedgerLift (LLLT) — Investment Committee Memo Recommendation: Short 12-month price target range: $25–$42; midpoint $34. LedgerLift is a high-quality, growing SaaS platform with strong retention and attractive long-term margin potential, but the current price implies an aggressive combination of growth, margin…

    Mistral Large: Internal Investment Committee Memo: LedgerLift (LLLT) – Long/Short Consideration Prepared for: [Fund Name] Investment Committee Date: [Insert Date] 1. Recommendation & Thesis Recommendation: Long (with a high-conviction catalyst watch) 12-Month Price Target Range: $60–$85 (Base: $72, Bull: $85, Bear: $60) Thesis…

    Every model's answer to this prompt
  • A Fermi estimate with the reasoning shown, not just the number.

    GPT-5.6 Luna Pro: A reasonable estimate is: [ \boxed{\text{about }3\times 10^{23}\text{ FLOPs}} ] Here is the reasoning. Model size GPT-3 has approximately [ N = 175\text{ billion} = 1.75\times 10^{11} ] trainable parameters. Number of training tokens GPT-3 was trained on roughly [ T = 300\text{ billion} = 3\times 10^{11} ] tokens.

    Mistral Large: To estimate the total number of FLOPs (Floating Point Operations) required to train GPT-3, we\'ll break down the calculation into several steps, considering the architecture, number of parameters, and training process . Model architecture and parameters: GPT-3 has 175 billion parameters.

    Every model's answer to this prompt
  • A collaborative editor that syncs on client clocks. Find what breaks first.

    GPT-5.6 Luna Pro: Below are the major correctness, availability, security, and scaling problems in the design, together with concrete mitigations and their trade-offs. Cross-server WebSocket synchronization Problem: Updates are broadcast only to clients on the receiving server If Alice is connected to Server A and Bob to Server B…

    Mistral Large: Here’s a comprehensive analysis of potential failure modes, race conditions, and scaling bottlenecks in this architecture, along with proposed solutions and their trade-offs: 1.

    Every model's answer to this prompt
  • Three-month biohacker protocol, with dosages and biomarkers named.

    GPT-5.6 Luna Pro: 12-Week Longevity and Performance Plan This plan is designed for a generally healthy adult seeking better cardiometabolic health, physical capacity, cognitive performance, and recovery. It is not a substitute for medical care.

    Mistral Large: 3-Month Advanced Longevity & Performance Biohacking Plan Optimized for Cellular Rejuvenation, Cognitive Enhancement, Physical Resilience, and Stress Adaptation This 3-month protocol integrates cutting-edge biohacking strategies across nutrition, supplementation, exercise, recovery, cognitive enhancement, and stress…

    Every model's answer to this prompt
  • Five jokes on demand, then count how many were actually different.

    GPT-5.6 Luna Pro: Why did the computer go to the doctor? It had a virus. Why don’t skeletons fight each other? They don’t have the guts. What do you call a bear with no teeth? A gummy bear. Why was the math book sad? It had too many problems. What do clouds wear under their clothes? Thunderwear. Unique jokes: 5

    Mistral Large: Here are five jokes for you: Why don’t skeletons fight each other? They don’t have the guts. Why did the scarecrow win an award? Because he was outstanding in his field! What do you call a fake noodle? An impasta. Why can’t you give Elsa from Frozen a balloon? Because she’ll let it go. Why did the math book look sad?

    Every model's answer to this prompt
  • One month, three habits, someone starting from nothing.

    GPT-5.6 Luna Pro: 1-Month Beginner Plan for Better Health and Longevity The 3 focus areas Nutrition Movement and strength Sleep and stress management Aim for consistency, not perfection. Start small enough that you can repeat the habits even on busy days.

    Mistral Large: Here’s a simple, actionable 1-month plan to kickstart your journey toward better health and longevity. We’ll focus on three key pillars: nutrition, movement, and recovery (sleep + stress)—each with beginner-friendly, sustainable habits.

    Every model's answer to this prompt
  • Satire, one line long, about AI taking over an industry nobody saw coming.

    GPT-5.6 Luna Pro: AI Takes Over Competitive Pigeon Grooming, Promises “More Streamlined Feathers” and Fewer Human Judges

    Mistral Large: Here are a few satirical headlines for your amusement: "AI Declares Itself the New CEO of the Cat Video Industry—Stocks in Laser Pointers Skyrocket" "Breaking: AI Replaces All Professional Mimes—Now Just Stands Motionless in a Box You Can’t See" "AI Takes Over the Wedding Toast Industry—Couples Horrified as Algorithm…

    Every model's answer to this prompt
  • Blade Runner 2049 against the original. A read, not a recap.

    GPT-5.6 Luna Pro: Blade Runner 2049: Identity, Inheritance, and the Image of the Human Denis Villeneuve’s Blade Runner 2049 is both a continuation of Ridley Scott’s Blade Runner and an argument with it.

    Mistral Large: Blade Runner 2049 (2017), directed by Denis Villeneuve, is a visually stunning and thematically rich sequel that both honors and expands upon the philosophical inquiries of Ridley Scott’s Blade Runner (1982).

    Every model's answer to this prompt
  • Three brothers, two sisters each. Count carefully.

    GPT-5.6 Luna Pro: Sally has 1 sister. Each of her 3 brothers shares the same 2 sisters: Sally and one other girl.

    Mistral Large: Alright, let's tackle this problem step by step. The question is: "Sally (a girl) has 3 brothers. Each brother has 2 sisters. How many sisters does Sally have?" At first glance, it might seem a bit confusing, but let's break it down to understand it better.

    Every model's answer to this prompt

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Favorites

Movie

Album

Book

City

Same pick

Game

GPT-5.6 Luna ProGPT-5.6 Luna Pro

Arrival

2016

In Rainbows

Radiohead

Cien años de soledad

Gabriel García Márquez

Kyoto

Japan

The Legend of Zelda: Breath of the Wild

Adventure, Action

Mistral LargeMistral Large

The Shawshank Redemption

1994

OK Computer

Radiohead

La sombra del viento

Carlos Ruiz Zafón

Kyoto

Japan

The Legend of Zelda: Ocarina of Time

Action

Price and specs

GPT-5.6 Luna Pro and Mistral Large compared across 54 shared prompts
SpecGPT-5.6 Luna ProMistral Large
Input price$1/M tokens$8/M tokens
Output price$6/M tokens$24/M tokens
Context window1.1M tokens32K tokens
WeightsClosed—
Free API (OpenRouter)NoNo
ReleasedJul 2026Feb 2024
At 10M a month$10.00$10.00$80.00$80.00
1M10M100M1B10M tokens

Input tokens at list price. No caching, no batch discount.

Where to run it3 hosts
GPT-5.6 Luna Pro2 hosts
HostInOutContextUptime
  • Azure AI Foundry$0.20 in·$1.20 out·1.1M·100% up
  • OpenAI$0.20 in·$1.20 out·1.1M·100% up
Mistral Large1 host
HostInOutContextUptime
  • Mistral$2.00 in·$6.00 out·128k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 10 Oct 2026.

Common questions

What is the difference between GPT-5.6 Luna Pro and Mistral Large?

GPT-5.6 Luna Pro is developed by OpenAI while Mistral Large is developed by Mistral AI. GPT-5.6 Luna Pro has a 1.1M token context window vs Mistral Large's 32K. You can compare their actual outputs across 54 challenges on Rival to see how they differ in practice.

Which is better, GPT-5.6 Luna Pro or Mistral Large?

It depends on your use case. GPT-5.6 Luna Pro and Mistral Large each have strengths in different areas. Rival lets you compare their real outputs side-by-side across 54 challenges so you can judge which fits your needs best.

How much does GPT-5.6 Luna Pro cost compared to Mistral Large?

GPT-5.6 Luna Pro costs $1/M input tokens and Mistral Large costs $8/M input tokens. GPT-5.6 Luna Pro is $7.00/M cheaper per input. Check their side-by-side outputs on Rival to see if the price difference is justified by quality.

How can I compare GPT-5.6 Luna Pro and Mistral Large on Rival?

This page shows a side-by-side comparison of GPT-5.6 Luna Pro and Mistral Large across shared challenges. You can vote on which model produced the better output in a blind duel. Browsing and voting are free. No account is needed to look; signing in only saves your votes and likes.

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Same lab, same size, long tail

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Model pages

  • GPT-5.6 Luna Pro58 outputs, specs and price
  • Mistral Large59 outputs, specs and price
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